We are happy to announce that a new R package, CMatching,  by Massimo Cannas, Elena Colicino and Bruno Arpino is available for download from CRAN.

CMatching provides functions to perform matching algorithms with clustered data, as described in:

 

Arpino B., and Cannas, M. (2016) Propensity score matching with clustered data. An application to the estimation of the impact of caesarean section on the Apgar score, Statistics in Medicine. 35(12), 2074–2091.

 

Pure within-cluster and preferential within-cluster matching are implemented. Both algorithms provide estimates of average treatment effects with cluster-adjusted standard errors.

 

The algorithms are useful to implement (propensity score) matching in the presence of multilevel data and can be used also to improve the balance of categorical covariates. For more detailed info on the package please see the attached reference manual.

 

The authors would be grateful to receive any feedback that might help improve the package in future releases. You can contact: Massimo Cannas ([email protected]) or Bruno Arpino ([email protected]).